[Remote] AI Research Engineer

Sourced from flexgen.zya.me

EnCharge AI is hiring an experienced AI Research Engineer to optimize deep learning models for deployment on edge AI platforms. The role focuses on model compression, quantization-aware training, and efficient inference techniques. You will work with PyTorch, ONNX Runtime, TVM, and collaborate with hardware engineers on edge AI chips. This is a remote position open to candidates in the USA.

• Research and develop quantization-aware training (QAT) and post-training quantization (PTQ) techniques for deep learning models
• Implement low-bit precision optimizations (e.g., INT8, BF16)
• Design and optimize efficient inference algorithms for AI workloads, focusing on latency, memory footprint, and power efficiency
• Work with frameworks such as PyTorch, ONNX Runtime, and TVM to deploy optimized models
• Analyze accuracy trade-offs and develop calibration techniques to mitigate precision loss in quantized models
• Collaborate with hardware engineers to optimize model execution for edge devices and NPUs
• Contribute to research on knowledge distillation, sparsity, pruning, and model compression techniques
• Benchmark performance across different hardware and software stacks
• Stay updated with the latest advancements in AI efficiency, model compression, and hardware acceleration